For Photovoltaic (PV) systems to operate at the Maximum Power Point (MPP) and maximize energy generation, a control mechanism known as Maximum Power Point Tracking (MPPT) is required. There are many MPPT methods avail...
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ISBN:
(数字)9798331530402
ISBN:
(纸本)9798331530419
For Photovoltaic (PV) systems to operate at the Maximum Power Point (MPP) and maximize energy generation, a control mechanism known as Maximum Power Point Tracking (MPPT) is required. There are many MPPT methods available. Because of their simplicity and cost efficiency, incremental conductance and perturb & observe methods are the most commonly utilized. But both the above-mentioned methods have common drawback that are fixed step-size and oscillations around MPP. To overcome this issue fuzzy logic controller (FLC) based MPPT is developed but it also suffers with steady-state oscillations around MPP. Hence in this paper, a new cascaded FLC-fractional proportional Integral derivative (FPID) controller based MPPT is proposed. In this, to study the performance of FLC-FPID a PV string with 4 S configuration is used. To test the proposed FLC-FPID MPPT a constant irradiance and variable irradiance conditions are used. The show the efficiency of proposed FLC-FPID approach is compared with FLC-PID and FLC. The proposed FLC-FPID approach outperforms the other two methods in terms tracking efficiency, oscillations at MPP, and tracking speed.
In the current context of the energy transition towards renewable and sustainable energy sources, solar energy is playing an increasingly crucial role, offering a clean and abundant solution to energy needs. However, ...
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Autonomous mobility systems face significant challenges related to privacy and large data volumes during the learning process. Vehicular Federated Learning (VFL) helps address these issues by protecting privacy and re...
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ISBN:
(数字)9798331521165
ISBN:
(纸本)9798331521172
Autonomous mobility systems face significant challenges related to privacy and large data volumes during the learning process. Vehicular Federated Learning (VFL) helps address these issues by protecting privacy and reducing data transmission. However, conventional methods often overlook real-world factors like client mobility and short roadside unit (RSU) timeouts. When clients move out of RSU coverage, model updates are disrupted, lowering learning efficiency. This paper introduces an Adaptive Timing control (ATC) method to optimize the transmission of client model gradients in VFL. Unlike traditional methods, ATC allows gradient aggregation regardless of server timeouts or client movement, letting clients upload gradients before leaving RSU coverage, even if calculations aren't complete. This method reduces data transmission volume by approximately 124 times compared to sending raw data and can potentially improve learning efficiency by approximately 40%. These improvements demonstrate the potential of ATC to enhance autonomous mobility systems in real-world environments.
In this paper use CIC-IDS2017 dataset to illustrate a comparative analysis of traditional and proposed models for intrusion detection in network security systems. The comparison includes DT, RF, ET and XGBoost classif...
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ISBN:
(数字)9798331512965
ISBN:
(纸本)9798331512972
In this paper use CIC-IDS2017 dataset to illustrate a comparative analysis of traditional and proposed models for intrusion detection in network security systems. The comparison includes DT, RF, ET and XGBoost classifiers. Normalize class, SMOTE Data preprocessing to compensate for missing values and of imbalance classes From the results of evaluation metrics, we conclude that proposed methods show a significant improvement on its model performances in detecting network intrusions as compared to traditional models XGboost specifically this work. Out of all the algorithms, the accuracy for XGBoost stands out, as it is mostly known to cater to complex attack patterns. The results indicate that ensemble base techniques offer the best solutions which can prove to be both effective and efficient as an intrusion detection systems for current network technologies.
This paper proposes a generalized dynamics model for a Non-Grounded System (NGS) mounted with a Reaction Force Sensing Series Elastic Actuator (RFSEA), focusing on scenarios where the actuator's base is unfixed an...
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ISBN:
(数字)9798331533892
ISBN:
(纸本)9798331533908
This paper proposes a generalized dynamics model for a Non-Grounded System (NGS) mounted with a Reaction Force Sensing Series Elastic Actuator (RFSEA), focusing on scenarios where the actuator's base is unfixed and interacts with the ground. In RFSEA-based force control, the actuator base, which provides the necessary reaction force as dictated by Newton's third law, plays a critical role. This study examines how the interaction between the actuator base and the ground it is attached to influences the response of the series elasticity that generates force in the RFSEA. The investigation involves two steps. First, a generalized dynamics model that considers the dynamics between the actuator base and the ground is derived. Second, the Small Gain Theorem (SGT) is applied to evaluate the robustness of force control under load-side model uncertainties when a Force-based Disturbance Observer (FDOB), originally designed for GS, is adapted to NGS. The analysis reveals that force control utilizing FDOB can become unstable when the actuator base is unfixed, and simulations validate these findings.
Concurrent engineering is based on the concept that different phases of a product life cycle should be conducted concurrently and initiated as early as possible within the Product Creation Process (PCP). Its main goal...
Concurrent engineering is based on the concept that different phases of a product life cycle should be conducted concurrently and initiated as early as possible within the Product Creation Process (PCP). Its main goal is to increase the efficiency and effectiveness of the PCP and reduce errors in the later stages, and to incorporate considerations for the full lifecycle, through-life operations, and environmental issues of the product. It has become the substantive basic methodology in many industries, and the initial basic concepts have matured and become the foundation of many new ideas, methodologies, initiatives, approaches and *** book presents the proceedings of the 24th ISPE Inc. internationalconference on Transdisciplinary (formerly: Concurrent) engineering (TE 2017), held in Singapore, in July 2017. The 120 peer-reviewed papers in the book are divided into 16 sections: air transport and traffic operations and management; risk-aware supply chain intelligence; product innovation and marketing management; human factors in design; human engineering; design methods and tools; decision supporting tools and methods; concurrent engineering; knowledge-based engineering; collaborative engineering; engineering for sustainability; service design; digital manufacturing; design automation; artificial intelligence and data analytics; smart systems and the Internet of *** book provides a comprehensive overview of recent advances in transdisciplinary concurrent engineering research and applications, and will be of interest to researchers, design practitioners and educators working in the field.
The highly dynamic new technology known as Vehicular Ad Hoc Networks (VANETs) supports wireless communication between hybrid vehicles. Wireless sensor networks’ (WSNs) technology is used by hybrid cars for a range of...
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The proceedings contain 81 papers. The topics discussed include: feedback control for buck converter - dc motor using observer;enhancement of electric vehicles integration into a real distribution network in Egypt;Bal...
ISBN:
(纸本)9781728130521
The proceedings contain 81 papers. The topics discussed include: feedback control for buck converter - dc motor using observer;enhancement of electric vehicles integration into a real distribution network in Egypt;Balun based transmitter leakage cancellation for wide-band applications;evaluation of gradient descent optimization method for SAR images co-registration;hyperbaric oxygen therapy for healing diabetic lower extremity ulcers;design and implementation of digital IF waveform generation, acquisition, and receiver circuits for radar systems applications;design and implementation of proposed low-cost dual-channel if receiver for SSR;and a study on the behavior and characteristics of a quartz tuning fork using finite element method.
Aiming at the problems of uncertainty of wind and photovoltaic power output and disorderly charging of a large number of electric vehicles accessing the distribution network leading to the superposition of distributio...
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ISBN:
(数字)9798331506797
ISBN:
(纸本)9798331506803
Aiming at the problems of uncertainty of wind and photovoltaic power output and disorderly charging of a large number of electric vehicles accessing the distribution network leading to the superposition of distribution network load peaks and the increase of network loss, a multi-timescale loss-reduction operation strategy of the distribution network considering electric vehicles is proposed. The probability distribution of EV behavior is established, and the EV charging output model conforming to the user's travel habit is built using the Latin hypercubic sampling method. Considering the influence of the deviation of the wind and photovoltaic output forecasts on different time scales, a multi-timescale optimal dispatch strategy based on the day-ahead-intraday is established, and a mathematical model is constructed by introducing the dynamic time-of-day tariff and using the network loss and the operating cost as the objective function. Different scenarios are simulated in the improved IEEE 33-bus system, and the comparative results show that the proposed optimization strategy is effective in reducing losses and smoothing load fluctuations, and the flexibility of EVs participating in the demand response of the grid reduces the impact of the wind and photovoltaic power integration while compensating for the deviation of the forecast of the wind and photovoltaic power outputs, thus maintaining the system balance.
One of the most pressing problems in world health today is the lack of accurate prediction models that can help with the early diagnosis and rapid treatment of cardiovascular disease. The primary focus of this study i...
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ISBN:
(数字)9798331512088
ISBN:
(纸本)9798331512095
One of the most pressing problems in world health today is the lack of accurate prediction models that can help with the early diagnosis and rapid treatment of cardiovascular disease. The primary focus of this study is to use machine learning techniques for the prediction of certain forms of cardiovascular illness, including Other Cardiovascular illness, Stable Angina, Coronary Artery Disease, and Unstable Angina. Age, sex, kind of chest pain, resting blood pressure, serum cholesterol, fasting blood sugar, and other important clinical diagnostic factors are included in the dataset. Current models that achieve 80% prediction accuracy include Logistic Regression and Naive Bayes. Unfortunately, they can't handle complex patterns in data and rely on linear assumptions, which limits their effectiveness. To enhance the precision of predictions, we advocate for the use of cutting-edge ML methods such as Random Forest and Gradient Boosting. Complex feature-nonlinear connection interactions are no match for these algorithms. Accuracy rates of 93% and 95%, respectively, have been achieved by these models by the use of their skills to tighten decision bounds and minimize errors via iterative learning. This research shows that these models have a chance to outperform the current system, providing clinicians with a reliable tool for better cardiac ailment classification, which would enhance healthcare choices and patient outcomes.
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